Evaluation & Testing

Ragas

Evaluate Retrieval Augmented Generation pipelines efficiently.

Status
Generally available
Last checked
Checked · Oct 10, 2026
License
Open source
Pricing
Free tier · from $0
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What it is

Ragas is a framework designed to help developers evaluate and improve their Retrieval Augmented Generation (RAG) pipelines, ensuring they meet performance and accuracy standards.

Ragas stands out as a specialized tool for evaluating Retrieval Augmented Generation pipelines, offering detailed metrics and customization options that are essential for optimizing these complex systems.

When it fits — and when it doesn’t

A good fit for

  • Teams building RAG apps who need a robust evaluation framework

  • Data scientists looking for customizable metrics to assess RAG performance

  • Developers aiming to optimize their retrieval and generation models

Look elsewhere if

  • Projects requiring real-time streaming capabilities (Ragas is batch-oriented)

  • Applications that do not involve RAG systems or similar technologies

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

  1. 01

    Limited support for non-Python models and retrieval systems

    Documentation focuses on Python-based frameworks like LangChain, Hugging Face Transformers

  2. 02

    Small community and limited third-party integrations

    GitHub issues have low activity, few external plugins or extensions available

What it does well

  • Comprehensive evaluation metrics for RAG pipelines

  • Integration with popular retrieval and generation models

  • Customizable evaluation scenarios

Pricing

Free tier
YesOpen source — free to use
Paid from
$0
Model
Flat rate
Enterprise plan
No

Pricing not independently confirmed — check the vendor’s page.

Performance benchmarks

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Set up Ragas

Setup steps, common gotchas and what to check after 30 days.

Open the setup guide →
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